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ICSE 2022
Sun 8 - Fri 27 May 2022
Mon 9 May 2022 20:05 - 20:10 at ICSE room 1-even hours - Machine Learning with and for SE 4 Chair(s): Gias Uddin
Thu 12 May 2022 13:10 - 13:15 at ICSE room 4-odd hours - Machine Learning with and for SE 12 Chair(s): Wei Yang
Fri 27 May 2022 11:20 - 11:25 at Room 301+302 - Papers 19: Machine Learning with and for SE 2 Chair(s): Dalal Alrajeh

Static code warning tools often generate warnings that programmers ignore. Such tools can be made more useful via data mining algorithms that select the “actionable” warnings; i.e. the warnings that are usually not ignored.

In this paper, we look for actionable warnings within a sample of 5,675 actionable warnings seen in 31,058 static code warnings from FindBugs. We find that data mining algorithms can find actionable warnings with remarkable ease. Specifically, a range of data mining methods (deep learners, random forests, decision tree learners, and support vector machines) all achieved very good results (recalls and AUC (TRN, TPR) measures usually over 95% and false alarms usually under 5%).

Given that all these learners succeeded so easily, it is appropriate to ask if there is something about this task that is inherently easy. We report that while our data sets have up to 58 raw features, those features can be approximated by less than two underlying dimensions. For such intrinsically simple data, many different kinds of learners can generate useful models with similar performance.

Based on the above, we conclude that learning to recognize actionable static code warnings is easy, using a wide range of learning algorithms, since the underlying data is intrinsically simple. If we had to pick one particular learner for this task, we would suggest linear SVMs (since, at least in our sample, that learner ran relatively quickly and achieved the best median performance) and we would not recommend deep learning (since this data is intrinsically very simple).

Mon 9 May

Displayed time zone: Eastern Time (US & Canada) change

20:00 - 21:00
Machine Learning with and for SE 4Journal-First Papers / Technical Track / SEIP - Software Engineering in Practice at ICSE room 1-even hours
Chair(s): Gias Uddin University of Calgary, Canada
20:00
5m
Talk
Revisiting Process versus Product Metrics: a Large Scale Analysi
Journal-First Papers
Suvodeep Majumder North Carolina State University, Pranav Mody North Carolina State University, Tim Menzies North Carolina State University
Link to publication DOI Pre-print Media Attached File Attached
20:05
5m
Talk
Learning to Recognize Actionable Static Code Warnings (is Intrinsically Easy)
Journal-First Papers
Xueqi Yang NCSU, Jianfeng Chen North Carolina State University, Rahul Yedida North Carolina State University, Zhe Yu , Tim Menzies North Carolina State University
Link to publication DOI Pre-print Media Attached
20:10
5m
Talk
Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps
SEIP - Software Engineering in Practice
Amrita Saha Salesforce Research Asia, Steven C.H. Hoi Salesforce Research Asia
Pre-print Media Attached
20:15
5m
Talk
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons
Technical Track
Xuanqi Gao Xi'an Jiaotong University, Juan Zhai Rutgers University, Shiqing Ma Rutgers University, Chao Shen Xi'an Jiaotong University, Yufei Chen Xi'an Jiaotong University, Qian Wang Wuhan University
DOI Pre-print Media Attached
20:20
5m
Talk
EREBA: Black-box Energy Testing of Adaptive Neural Networks
Technical Track
Mirazul Haque UT Dallas, Yaswanth Yadlapalli University of Texas at Dallas, Wei Yang University of Texas at Dallas, Cong Liu University of Texas at Dallas, USA
Pre-print Media Attached
20:25
5m
Talk
Training Data Debugging for the Fairness of Machine Learning Software
Technical Track
Yanhui Li Department of Computer Science and Technology, Nanjing University, Linghan Meng Nanjing University, Lin Chen Department of Computer Science and Technology, Nanjing University, Li Yu Nanjing University, Di Wu Momenta, Yuming Zhou Nanjing University, Baowen Xu Nanjing University
Pre-print Media Attached

Thu 12 May

Displayed time zone: Eastern Time (US & Canada) change

13:00 - 14:00
Machine Learning with and for SE 12Journal-First Papers / Technical Track / NIER - New Ideas and Emerging Results at ICSE room 4-odd hours
Chair(s): Wei Yang University of Texas at Dallas
13:00
5m
Talk
Modeling Functional Similarity in Source Code with Graph-Based Siamese Networks
Journal-First Papers
NIKITA MEHROTRA Indraprastha Institute of Information Technology, NAVDHA AGARWAL Indraprastha Institute of Information Technology, Delhi, PIYUSH GUPTA Indraprastha Institute of Information Technology, Delhi, SAKET ANAND Indraprastha Institute of Information Technology, Delhi, David Lo Singapore Management University, Rahul Purandare IIIT-Delhi
Link to publication DOI Media Attached
13:05
5m
Talk
Revisiting Process versus Product Metrics: a Large Scale Analysi
Journal-First Papers
Suvodeep Majumder North Carolina State University, Pranav Mody North Carolina State University, Tim Menzies North Carolina State University
Link to publication DOI Pre-print Media Attached File Attached
13:10
5m
Talk
Learning to Recognize Actionable Static Code Warnings (is Intrinsically Easy)
Journal-First Papers
Xueqi Yang NCSU, Jianfeng Chen North Carolina State University, Rahul Yedida North Carolina State University, Zhe Yu , Tim Menzies North Carolina State University
Link to publication DOI Pre-print Media Attached
13:15
5m
Talk
Improving the Learnability of Machine Learning APIs by Semi-Automated API Wrapping
NIER - New Ideas and Emerging Results
Lars Reimann University of Bonn, Günter Kniesel-Wünsche University of Bonn
DOI Pre-print Media Attached
13:20
5m
Talk
Improving Machine Translation Systems via Isotopic Replacement
Technical Track
Zeyu Sun Peking University, Jie M. Zhang King's College London, Yingfei Xiong Peking University, Mark Harman University College London, Mike Papadakis University of Luxembourg, Luxembourg, Lu Zhang Peking University
Pre-print Media Attached
13:25
5m
Talk
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and ProcessDistinguished Paper Award
Technical Track
Nadia Nahar Carnegie Mellon University, Shurui Zhou University of Toronto, Grace Lewis Carnegie Mellon Software Engineering Institute, Christian Kästner Carnegie Mellon University
Pre-print Media Attached

Fri 27 May

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Papers 19: Machine Learning with and for SE 2Journal-First Papers / Technical Track at Room 301+302
Chair(s): Dalal Alrajeh Imperial College London
11:00
5m
Talk
Defect Reduction Planning (using TimeLIME)
Journal-First Papers
Kewen Peng North Carolina State University, Tim Menzies North Carolina State University
Authorizer link Pre-print Media Attached
11:05
5m
Talk
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
Technical Track
Qibin Chen Carnegie Mellon University, Jeremy Lacomis Carnegie Mellon University, Edward J. Schwartz Carnegie Mellon University Software Engineering Institute, Graham Neubig Carnegie Mellon University, Bogdan Vasilescu Carnegie Mellon University, USA, Claire Le Goues Carnegie Mellon University
DOI Pre-print Media Attached
11:10
5m
Talk
EREBA: Black-box Energy Testing of Adaptive Neural Networks
Technical Track
Mirazul Haque UT Dallas, Yaswanth Yadlapalli University of Texas at Dallas, Wei Yang University of Texas at Dallas, Cong Liu University of Texas at Dallas, USA
Pre-print Media Attached
11:15
5m
Talk
Multilingual training for Software Engineering
Technical Track
Toufique Ahmed University of California at Davis, Prem Devanbu Department of Computer Science, University of California, Davis
DOI Pre-print Media Attached
11:20
5m
Talk
Learning to Recognize Actionable Static Code Warnings (is Intrinsically Easy)
Journal-First Papers
Xueqi Yang NCSU, Jianfeng Chen North Carolina State University, Rahul Yedida North Carolina State University, Zhe Yu , Tim Menzies North Carolina State University
Link to publication DOI Pre-print Media Attached
11:25
5m
Talk
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and ProcessDistinguished Paper Award
Technical Track
Nadia Nahar Carnegie Mellon University, Shurui Zhou University of Toronto, Grace Lewis Carnegie Mellon Software Engineering Institute, Christian Kästner Carnegie Mellon University
Pre-print Media Attached
11:30
5m
Talk
Lessons Learnt on Reproducibility in Machine Learning Based Android Malware Detection
Journal-First Papers
Nadia Daoudi SnT, University of Luxembourg, Kevin Allix University of Luxembourg, Tegawendé F. Bissyandé SnT, University of Luxembourg, Jacques Klein University of Luxembourg
Link to publication Pre-print Media Attached

Information for Participants
Mon 9 May 2022 20:00 - 21:00 at ICSE room 1-even hours - Machine Learning with and for SE 4 Chair(s): Gias Uddin
Info for room ICSE room 1-even hours:

Click here to go to the room on Midspace

Thu 12 May 2022 13:00 - 14:00 at ICSE room 4-odd hours - Machine Learning with and for SE 12 Chair(s): Wei Yang
Info for room ICSE room 4-odd hours:

Click here to go to the room on Midspace